Results 71 to 80 of about 10,108 (225)
Procedia Computer Science, 2015 AbstractDespite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era.
Craig M. Vineyard +4 more
openaire +1 more source
Adaptive Combiner for MapReduce on cloud computing
, 2014 MapReduce is a programming model to process a massive amount of data on cloud computing. MapReduce processes data in two phases and needs to transfer intermediate data among computers between phases. MapReduce allows programmers to aggregate intermediate
Lee, Wei-Tsong
core +1 more source
Primitive per l'Analisi di Grandi Grafi in MapReduce [PDF]
, 2022 I grafi sono strutture utilizzate in ogni ambito. Per l’analisi di grafi sempre più grandi è necessario sviluppare degli algoritmi paralleli. MapReduce è un modello di computazione che permette di sviluppare in modo semplice algoritmi efficienti che ...
Parigi Bini, Gianmaria
core
Design of a TSK Rule‐Based Model With Granular Rules and Ensemble Learning in Big Data
Complexity, Volume 2026, Issue 1, 2026.Nowadays, the management and analysis of big data have become major challenges for researchers in the field of data mining. The increasing rate of data generation, along with the need to extract meaningful patterns, highlights the necessity of developing scalable big data analysis methods.
Mohammad Nematpour +4 more
wiley +1 more source
Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source
Finding Top- $k$ Dominance on Incomplete Big Data Using MapReduce Framework
IEEE Access, 2018 Incomplete data is one major kind of multi-dimensional dataset that has random-distributed missing nodes in its dimensions. It is very difficult to retrieve information from this type of dataset when it becomes large.
Payam Ezatpoor +3 more
doaj +1 more source
Anti-combining for MapReduce [PDF]
Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, 2014 We propose Anti-Combining, a novel optimization for MapReduce programs to decrease the amount of data transferred from mappers to reducers. In contrast to Combiners, which decrease data transfer by performing reduce work on the mappers, Anti-Combining shifts mapper work to the reducers.
Alper Okcan, Mirek Riedewald
openaire +1 more source
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.With the deepening of industrial digital transformation, equipment fault diagnosis faces challenges including low utilization of unstructured data, weak cross‐modal semantic association, and lagging knowledge updates. Traditional methods relying on artificial rules and static knowledge bases struggle to effectively integrate multimodal information such
Yu Fang, Richard Murray
wiley +1 more source
Canadian Journal of Statistics, Volume 53, Issue 4, December 2025.Abstract Modern longitudinal data from wearable devices consist of biological signals at high‐frequency time points. Distributed statistical methods have emerged as a powerful tool to overcome the computational burden of estimation and inference with large data, but methodology for distributed functional regression remains limited.
Cole Manschot, Emily C. Hector
wiley +1 more source
MapReduce: within, outside, or on the side-by-side with parallel DBMSs?
Труды Института системного программирования РАН, 2018 The approaches of use of MapReduce technology together with analytical DBMSs are discussed. The paper considers approaches where one implements MapReduce within a kernel of a parallel DBMS, where MapReduce serves as a communication infrastructure of a ...
Sergey D. Kuznetsov.
doaj